We consider the problem of eliminating redundant Boolean
features for a given data set, where a feature is redundant if it
separates the classes less well than another feature or set of
features. Lavrač et al. proposed the algorithm Reduce that works
by pairwise comparison of features, i.e., it eliminates a feature if
it is redundant with respect to another feature. Their algorithm
operates in an ILP setting and is restricted to two-class problems.
In this paper we improve their method and extend it to multiple
classes. Central to our approach is the notion of a neighbourhood
of examples: a set of examples of the same class where the number
of different features between examples is relatively small. Redundant
features are eliminated by applying a revised version of the Reduce
method to each pair of neighbourhoods of different class. We analyse
the performance of our method on a range of data sets.